We perform a Bayesian parameter estimation analysis [1]} to measure the source properties of the seven binary black-mergers from Advanced LIGO–Virgo's second observing run, using the gravitational-wave data available at the Gravitational-Wave Open Science Center [2]}. We use the data available from the Advanced LIGO detectors for GW170104, GW170608, GW170823. For GW170729, GW170809, GW170814, and GW170818, we use the available Advanced LIGO and the Advanced Virgo data. The parameter estimation analysis was executed using the PyCBC Inference software [3]}, [4]} and the parallel-tempered emcee sampler [5]}, [6]}, [7]}, which employs ensemble Markov chain Monte Carlo (MCMC) techniques [8]}, [9]}, [10]}, [1]}, [12]}, [13]}, [14]}, [15]}, [16]}, [17]}, [18]} to sample the posterior probability density function \(p(\vec{\vartheta }|\vec{d}(t),H)\) . We calculate the posterior probability density function, \(p(\vec{\vartheta }|\vec{d}(t),H)\) , for the set of parameters \(\vec{\vartheta }\)  for the gravitational-waveform model, \(H\) , given the gravitational-wave data from the detectors \(\vec{d}(t)\)  [2]}
\( p(\vec{\vartheta }|\vec{d}(t),H)=\frac{p(\vec{d}(t)|\vec{\vartheta },H)p(\vec{\vartheta }|H)}{p(\vec{d}(t)|H)} ,\) 
